LOG_DIR="logs"
EXPNAME="DiffOGMP_vae2d"          # experiment name 

CONFIG="configs/autoencoders/basic_vae.yaml"
# OR CONFIG="configs/videoae/ucf.yaml"
# OR CONFIG="configs/videoae/taichi.yaml"

# run
python main.py \
--base $CONFIG \
-t --gpus "0,1" \
--logdir $LOG_DIR \
# --resume logs/2024-12-04T18-46-40_autoencoderkl_8x8x8/checkpoints/last.ckpt
# --name $EXPNAME \

# -------------------------------------------------------------------------------------------------
# commands for multi nodes training     
# - use torch.distributed.run to launch main.py
# - set `gpus` and `lightning.trainer.num_nodes`

# For example:

# python -m torch.distributed.run \
#     --nproc_per_node=8 --nnodes=$NHOST --master_addr=$MASTER_ADDR --master_port=1234 --node_rank=$INDEX \
#     main.py \
#     --base $CONFIG \
#     -t --gpus 0,1,2,3,4,5,6,7 \
#     --name $EXPNAME \
#     --logdir $PROJ_ROOT \
#     --auto_resume True \
#     lightning.trainer.num_nodes=$NHOST \
#     data.params.train.params.data_root=$DATADIR \
#     data.params.validation.params.data_root=$DATADIR
